Martin Linstrom, MD at IPsoft is today’s guest columnist, with a viewpoint on how Artificial Intelligence can improve comms between customer and insurer, or broker. The future is virtual.

If your company handles insurance-related customer interactions, it’s time to consider Artificial Intelligence (AI). In one consumer study, 74% of consumers say they would take insurance advice from a virtual assistant, while a similar percentage of insurance executives expect AI to improve business.

However, as with any emerging technology, some companies have been slow to adopt AI into customer-facing activities. That’s because many executives don’t fully understand how beneficial AI can be to their business. Almost 40% of all practitioners who have not yet invested in AI don’t know where AI can be used in their business, according to Deloitte.

To explore how AI can enable better customer interactions for insurers, we explore three key considerations for insurers that are thinking about implementing AI for customer services.

Martin Linstrom

What service do I want to provide?

The first hurdle for any business when determining whether AI can improve customer interactions is deciding what level of service they want to provide. There are a number of different types of digital assistants on the market – and not all bots are made equal.

Insurers can easily find themselves comparing apples and pears when looking at AI solutions. So, it’s critical to start by looking at the different available solutions – from static chatbots, to cognitive AI agents – to consider the benefits of each solution and determine which can deliver the best experience to their customers.

Cognitive agents use advanced Natural Language Understanding (NLU) to navigate complex and foreign words and phrases to converse with customers. Unlike static chatbots, cognitive agents go beyond words to determine user intent. Once they determine a customer’s intent or intents, cognitive agents can handle multiple contexts within one conversation. This delivers a more complex, prolonged, and multi-stage conversations.

Cognitive agents can also be trained to gain a specialised understanding of a certain marketplace, and adapt to the role, so they can respond to customer questions across a wide variety of subject areas, including renters, property, marine, auto, and life insurance.

Chatbots don’t offer this level of sophistication. They operate from programmed scripts that allow them to complete basic tasks. If customers veer from this script or use language that is foreign to the chatbots, it will immediately escalate the transaction to a human colleague. This extends the interaction unnecessarily and creates a frustrating customer experience.

Finally, many customer engagements for insurers come at difficult moments in their lives. They may have just been burgled, a relative may have died, or they could have just had a car accident. It’s therefore important for any automated solution to recognise and react to the emotional state of the customer. Some cognitive AI agents also have emotional intelligence built in, allowing them to understand the customers’ tone and mood throughout the interaction. This enables it to display empathy and detects sentiment in order to reassure customers with appropriate phrases and comments when needed.

How can a cognitive agent help?

Every deployment of a cognitive agent is unique, so insurers need to think about the best way that a cognitive agent can help them and their employees. Here are just a few ways that cognitive agents can be deployed in an organisation:

Always-on customer care

Cognitive agents’ services can be delivered across multiple channels (web, phone, text, chat, etc.) 24/7/365, providing limitless support capacity. This ensures a customer never waits long for quality service even during spikes in customer call volume.

In fact, IPsoft’s Amelia’s transactional processing and scaling ability has enabled insurers to reduce their support costs by up to one-third and reinvest those savings back into the business. Because of her scalability, transaction and support resolution, times are drastically reduced. She can also reach accuracy levels in excess of 95% in managing certain conversations and policy transactions.

Exemplary executor

Cognitive agents are expert at gathering, verifying, and processing customer information. When customer facing, this enables them to have natural conversations with customers about insurance needs and personal habits in order to offer policy information and quotes.

With their deeper industry understanding and ability to engage in a real dialogue, Cognitive AI agents can make recommendations and execute transactions faster than humans with a personalised touch. This typically eliminates the need for a customer to visit an agent’s office or make a support call, as the cognitive agent can handle most frequent customer queries and transactions, such as incident registrations, policy recommendations, deductible and payment inquiries, rider recommendations, and a whole lot more.

The whisper agent

Cognitive agents’ ability to learn and improve over time helps them collaborate with human customer service colleagues, unlike static, low-level chatbots.

Non-licensed agents are not permitted to advise on or sell certain products and services. When those agents receive a call and need to service a customer, they can quickly interact with the cognitive agent behind the scenes and determine whether they can assist that customer. If they can, the cognitive agent uses its knowledge to coach the agent through the customer engagement; if not, the cognitive agent helps the human agent refer the customer to a colleague who can.

In the end, the customer receives correct information and an efficient service experience, the agent is confident that they’ve done the right thing, and the company knows their employees are complying with all proper and legal procedures.

Fraud detection

With their advanced analytics, cognitive agents can also analyse a customer’s submitted information and help human agents determine whether the data is up-to-date and accurate. This then allows them to make recommendations on whether a policy should be issued, for what amount and at what premium level. As knowledge is accumulated over time, cognitive agents are well placed to recognise anomalies that may indicate fraud and report them to their human colleagues.

Does it really work?

There’s no question that cognitive agents hold all the promise for better customer interactions in insurance. But the million-dollar question is “does it really work?”.

One large insurer seeing the benefits of using cognitive agents to support their customer interactions is Allstate. The largest publicly held personal lines insurer in the US, Allstate first deployed cognitive AI agent, Amelia in September 2017. She has collaborated with Allstate live agents on more than three million calls. She leads agents through step-by-step procedures on a variety of support issues, including policy details and policyholder information.

Trained on almost 40 different insurance topics for Allstate, Amelia has lowered call duration from 4.6 to 4.2 minutes and 75% of customer inquiries have been solved during the first call, compared with 67% prior to Amelia’s hiring. In one month alone, Amelia assisted on almost 250,000 calls. Also, 99% of Allstate agents who worked with Amelia said they were completely satisfied with their interactions with her.

What are you waiting for?

Cognitive agents are a proven, enterprise-ready and scalable solution that are taking insurers’ customer interactions to the next level. Those insurers that have already invested are taking advantage of the competitive edge that it has given them against other companies that are hesitant about making investments in AI.

But given the current market trends and shifting consumer tastes, it won’t be long before customer expect and demand the always-on and superior service that cognitive agents provide both directly and behind the scenes. The hybrid workforce of human and digital agents is the future of customer engagements, so now is the time for insurers to investigate and invest in AI is now.